Evaluation of SIMMARC: An Audiovisual System for the Detection of Near-Miss Accidents

Florian Krebs; Georg Thallinger; Helmut Neuschmied; Franz Graf; Georg Huber; Kurt Fallast; Peter Vertal; Eduard Kolla

Intelligent Transport Systems. From Research and Development to the Market Uptake. Third EAI International Conference, INTSYS 2019, Braga, Portugal, December 4–6, 2019

Research Article

Evaluation of SIMMARC: An Audiovisual System for the Detection of Near-Miss Accidents

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@INPROCEEDINGS{10.1007/978-3-030-38822-5_13,
    author={Florian Krebs and Georg Thallinger and Helmut Neuschmied and Franz Graf and Georg Huber and Kurt Fallast and Peter Vertal and Eduard Kolla},
    title={Evaluation of SIMMARC: An Audiovisual System for the Detection of Near-Miss Accidents},
    proceedings={Intelligent Transport Systems. From Research and Development to the Market Uptake. Third EAI International Conference, INTSYS 2019, Braga, Portugal, December 4--6, 2019},
    proceedings_a={INTSYS},
    year={2020},
    month={1},
    keywords={Near-miss accidents Accident detection Automatic event detection},
    doi={10.1007/978-3-030-38822-5_13}
}

Florian Krebs
Georg Thallinger
Helmut Neuschmied
Franz Graf
Georg Huber
Kurt Fallast
Peter Vertal
Eduard Kolla
Year: 2020
Evaluation of SIMMARC: An Audiovisual System for the Detection of Near-Miss Accidents
INTSYS
Springer
DOI: 10.1007/978-3-030-38822-5_13

Florian Krebs¹^,*, Georg Thallinger¹, Helmut Neuschmied¹, Franz Graf¹, Georg Huber², Kurt Fallast², Peter Vertal³, Eduard Kolla³

1: Joanneum Research
2: Planum
3: University of Žilina

*Contact email: florian.krebs@joanneum.at

Abstract

In this paper, we present and evaluate a system that automatically identifies hazardous traffic situations using visual and acoustic sensors. The system has been installed at three locations in Austria and several months of audio and video data have been analyzed. We evaluate the accuracy of the employed data analysis algorithms as well as the usefulness of the detected events for the overall task of assessing the risk potential of a road intersection. Our results show that the long-term analysis made possible by the proposed system leads to a better understanding of the risk potential of traffic areas, and can finally serve as a basis for defining and prioritizing improvements.

Keywords: Near-miss accidents Accident detection Automatic event detection

Published: 2020-01-10
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-030-38822-5_13